Predicting Pediatric Age-Matched Weight and Body Mass Index

被引:0
作者
Sherwin K. B. Sy
Eduardo Asin-Prieto
Hartmut Derendorf
Emil Samara
机构
[1] University of Florida,Department of Pharmaceutics, College of Pharmacy
[2] PharmaPolaris International,undefined
来源
The AAPS Journal | 2014年 / 16卷
关键词
Age; Allometry; BMI; Pediatric; Weight;
D O I
暂无
中图分类号
学科分类号
摘要
The empirical scaling from adult to pediatric using allometric size adjustments based on body weight continued to be the mainstream method for pediatric dose selection. Due to the flexibility of a polynomial function to conform to the data trend, an empirical function for simulating age-matched weight and body mass index by gender in the pediatric population is developed by using a polynomial function and a constant coefficient to describe the interindividual variability in weight. A polynomial of up to fifth order sufficiently described the pediatric data from the Center for Disease Control (CDC) and the World Health Organization (WHO). The coefficients of variation to describe the variability were within 17%. The percentages of the CDC simulated weights for pediatrics between 0 and 5 years that fell outside the WHO 90% and 95% confidence boundaries were well within the expected percentage values, indicating that the CDC dataset can be used to substitute for the WHO dataset for the purpose of pediatric drug development. To illustrate the utility of this empirical function, the CDC-based age-matched weights were simulated and were used in the prediction of the concentration–time profiles of tenofovir in children based on a population pharmacokinetic model whose parameters were allometrically scaled. We have shown that the resulting 95% prediction interval of tenofovir in newborn to 5 years of age was almost identical whether the weights were simulated based on WHO or CDC dataset. The approach is simple and is broadly applicable in adjusting for pediatric dosages using allometry.
引用
收藏
页码:1372 / 1379
页数:7
相关论文
共 62 条
[1]  
West GB(1997)A general model for the origin of allometric scaling laws in biology Science 276 122-126
[2]  
Brown JH(2001)Allometric scaling of xenobiotic clearance: uncertainty versus universality AAPS PharmSci 3 E29-282
[3]  
Enquist BJ(2004)The predominance of quarter‐power scaling in biology Funct Ecol 18 257-2534
[4]  
Hu TM(2004)A comprehensive analysis of the role of correction factors in the allometric predictivity of clearance from rat, dog, and monkey to humans J Pharm Sci 93 2522-557
[5]  
Hayton WL(2006)Prediction of drug clearance in children from adults: a comparison of several allometric methods Br J Clin Pharmacol 61 545-227
[6]  
Savage VM(1982)Interspecies scaling, allometry, physiological time, and the ground plan of pharmacokinetics J Pharmacokinet Biopharm 10 201-1121
[7]  
Gillooly J(1984)Interspecies pharmacokinetic scaling and the evolutionary-comparative paradigm Drug Metab Rev 15 1071-332
[8]  
Woodruff W(1996)A size standard for pharmacokinetics Clin Pharmacokinet 30 329-278
[9]  
West G(2007)Prediction of drug clearance in children: impact of allometric exponents, body weight, and age Ther Drug Monit 29 271-603
[10]  
Allen A(2010)What is the right dose for children? Br J Clin Pharmacol 70 597-454